dc.contributor.author | Parangusam, Kanakaraj | |
dc.contributor.author | Lekshmana, Ramesh | |
dc.contributor.author | Goňo, Tomáš | |
dc.contributor.author | Goňo, Radomír | |
dc.date.accessioned | 2024-04-16T11:49:54Z | |
dc.date.available | 2024-04-16T11:49:54Z | |
dc.date.issued | 2023 | |
dc.identifier.citation | Energies. 2023, vol. 16, issue 18, art. no. 6681. | cs |
dc.identifier.issn | 1996-1073 | |
dc.identifier.uri | http://hdl.handle.net/10084/152504 | |
dc.description.abstract | Electricity demand has increased tremendously in recent years, due to the fact that all
sectors require energy for their operation. Due to the increased amount of modern home appliances
on the market, residential areas consume a significant amount of energy. This article focuses on
the residential community to reduce peak load on residential distribution networks. Mostly, the
residential consumer’s power demand increases more during the summer season due to many air
conditioners (AC) operating in residential homes. This paper proposes a novel summer peak intelli gent controller (SPIC) algorithm to reduce summer peak load in residential distribution transformers
(RDT). This proposed SPIC algorithm is implemented in a multi-home energy management system
(MHEMS) with a four-home hardware prototype and a real-time TNEB system. This hardware
prototype is divided into two different cases, one with and one without taking user comfort into
account. When considering consumer comfort, all residential homes reduce their peak load almost
equally. The maximum and minimum contribution percentages in Case 2 are 29.82% and 19.30%,
respectively. Additionally, the real-time TNEB system is addressed in two different cases: with and
without incentive-based programs. In the real-time TNEB system during peak hours, the novel SPIC
algorithm reduces peak demand in Case 1 by 113.70 kW, and Case 2 further reduces it to 118.80 kW.
The peak load decrease in Case 2 during peak hours is 4.5% greater than in Case 1. In addition, we
conducted a residential consumer opinion survey to validate the acceptance rate of the proposed
design and algorithm. | cs |
dc.language.iso | en | cs |
dc.publisher | MDPI | cs |
dc.relation.ispartofseries | Energies | cs |
dc.relation.uri | https://doi.org/10.3390/en16186681 | cs |
dc.rights | © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. | cs |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | cs |
dc.subject | multi-home energy management system (MHEMS) | cs |
dc.subject | residential distribution transformer (RDT) | cs |
dc.subject | summer peak intelligent controller (SPIC) | cs |
dc.subject | demand side management (DSM) | cs |
dc.subject | Tamil Nadu Electricity Board (TNEB) | cs |
dc.subject | Python | cs |
dc.subject | energy management | cs |
dc.title | Evolution of a summer peak intelligent controller (SPIC) for residential distribution networks | cs |
dc.type | article | cs |
dc.identifier.doi | 10.3390/en16186681 | |
dc.rights.access | openAccess | cs |
dc.type.version | publishedVersion | cs |
dc.type.status | Peer-reviewed | cs |
dc.description.source | Web of Science | cs |
dc.description.volume | 16 | cs |
dc.description.issue | 18 | cs |
dc.description.firstpage | art. no. 6681 | cs |
dc.identifier.wos | 001081857000001 | |